Alejandro Reyes

Detecting differential usage of exons from RNA-seq data

RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package.

Direct Competition between hnRNP C and U2AF65 Protects the Transcriptome from the Exonization of Alu Elements

Summary There are ∼650,000 Alu elements in transcribed regions of the human genome. These elements contain cryptic splice sites, so they are in constant danger of aberrant incorporation into mature transcripts. Despite posing a major threat to transcriptome integrity, little is known about the molecular mechanisms preventing their inclusion. Here, we present a mechanism for protecting the human transcriptome from the aberrant exonization of transposable elements. Quantitative iCLIP data show that the RNA-binding protein hnRNP C competes with the splicing factor U2AF65 at many genuine and cryptic splice sites. Loss of hnRNP C leads to formation of previously suppressed Alu exons, which severely disrupt transcript function. Minigene experiments explain disease-associated mutations in Alu elements that hamper hnRNP C binding. Thus, by preventing U2AF65 binding to Alu elements, hnRNP C plays a critical role as a genome-wide sentinel protecting the transcriptome. The findings have important implications for human evolution and disease.

Identification of Regulatory Networks in HSCs and Their Immediate Progeny via Integrated Proteome, Transcriptome, and DNA Methylome Analysis

In this study, we present integrated quantitative proteome, transcriptome, and methylome analyses of hematopoietic stem cells (HSCs) and four multipotent progenitor (MPP) populations. From the characterization of more than 6,000 proteins, 27,000 transcripts, and 15,000 differentially methylated regions (DMRs), we identified coordinated changes associated with early differentiation steps. DMRs show continuous gain or loss of methylation during differentiation, and the overall change in DNA methylation correlates inversely with gene expression at key loci. Our data reveal the differential expression landscape of 493 transcription factors and 682 lncRNAs and highlight specific expression clusters operating in HSCs. We also found an unexpectedly dynamic pattern of transcript isoform regulation, suggesting a critical regulatory role during HSC differentiation, and a cell cycle/DNA repair signature associated with multipotency in MPP2 cells. This study provides a comprehensive genome-wide resource for the functional exploration of molecular, cellular, and epigenetic regulation at the top of the hematopoietic hierarchy.

Myc depletion induces a pluripotent dormant state mimicking diapause

Summary Mouse embryonic stem cells (ESCs) are maintained in a naive ground state of pluripotency in the presence of MEK and GSK3 inhibitors. Here, we show that ground-state ESCs express low Myc levels. Deletion of both c-myc and N-myc (dKO) or pharmacological inhibition of Myc activity strongly decreases transcription, splicing, and protein synthesis, leading to proliferation arrest. This process is reversible and occurs without affecting pluripotency, suggesting that Myc-depleted stem cells enter a state of dormancy similar to embryonic diapause. Indeed, c-Myc is depleted in diapaused blastocysts, and the differential expression signatures of dKO ESCs and diapaused epiblasts are remarkably similar. Following Myc inhibition, pre-implantation blastocysts enter biosynthetic dormancy but can progress through their normal developmental program after transfer into pseudo-pregnant recipients. Our study shows that Myc controls the biosynthetic machinery of stem cells without affecting their potency, thus regulating their entry and exit from the dormant state.

Single-cell transcriptome analysis reveals coordinated ectopic gene-expression patterns in medullary thymic epithelial cells

Expression of tissue-restricted self antigens (TRAs) in medullary thymic epithelial cells (mTECs) is essential for the induction of self-tolerance and prevents autoimmunity, with each TRA being expressed in only a few mTECs. How this process is regulated in single mTECs and is coordinated at the population level, such that the varied single-cell patterns add up to faithfully represent TRAs, is poorly understood. Here we used single-cell RNA sequencing and obtained evidence of numerous recurring TRA–co-expression patterns, each present in only a subset of mTECs. Co-expressed genes clustered in the genome and showed enhanced chromatin accessibility. Our findings characterize TRA expression in mTECs as a coordinated process that might involve local remodeling of chromatin and thus ensures a comprehensive representation of the immunological self.

Transcriptome-wide profiling and posttranscriptional analysis of hematopoietic stem/progenitor cell differentiation toward myeloid commitment

Summary Hematopoietic stem cells possess lifelong self-renewal activity and generate multipotent progenitors that differentiate into lineage-committed and subsequently mature cells. We present a comparative transcriptome analysis of ex vivo isolated mouse multipotent hematopoietic stem/progenitor cells (LinnegSCA-1+c-KIT+) and myeloid committed precursors (LinnegSCA-1negc-KIT+). Our data display dynamic transcriptional networks and identify a stem/progenitor gene expression pattern that is characterized by cell adhesion and immune response components including kallikrein-related proteases. We identify 498 expressed lncRNAs, which are potential regulators of multipotency or lineage commitment. By integrating these transcriptome with our recently reported proteome data, we found evidence for posttranscriptional regulation of processes including metabolism and response to oxidative stress. Finally, our study identifies a high number of genes with transcript isoform regulation upon lineage commitment. This in-depth molecular analysis outlines the enormous complexity of expressed coding and noncoding RNAs and posttranscriptional regulation during the early differentiation steps of hematopoietic stem cells toward the myeloid lineage.

Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues

Abstract Most human genes generate multiple transcript isoforms. The differential expression of these isoforms can help specify cell types. Diverse transcript isoforms arise from the use of alternative transcription start sites, polyadenylation sites and splice sites; however, the relative contribution of these processes to isoform diversity in normal human physiology is unclear. To address this question, we investigated cell type-dependent differences in exon usage of over 18 000 protein-coding genes in 23 cell types from 798 samples of the Genotype-Tissue Expression Project. We found that about half of the expressed genes displayed tissue-dependent transcript isoforms. Alternative transcription start and termination sites, rather than alternative splicing, accounted for the majority of tissue-dependent exon usage. We confirmed the widespread tissue-dependent use of alternative transcription start sites in a second, independent dataset, Cap Analysis of Gene Expression data from the FANTOM consortium. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not increase proteome complexity. Thus, alternative transcription start and termination sites are the principal drivers of transcript isoform diversity across tissues, and may underlie the majority of cell type specific proteomes and functions.

RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking

BackgroundCigarette smoking is the leading modifiable risk factor for disease and death worldwide. Previous studies quantifying gene-level expression have documented the effect of smoking on mRNA levels. Using RNA sequencing, it is possible to analyze the impact of smoking on complex regulatory phenomena (e.g. alternative splicing, differential isoform usage) leading to a more detailed understanding of the biology underlying smoking-related disease.MethodsWe used whole-blood RNA sequencing to describe gene and exon-level expression differences between 229 current and 286 former smokers in the COPDGene study. We performed differential gene expression and differential exon usage analyses using the voom/limma and DEXseq R packages. Samples from current and former smokers were compared while controlling for age, gender, race, lifetime smoke exposure, cell counts, and technical covariates.ResultsAt an adjusted p-value <0.05, 171 genes were differentially expressed between current and former smokers. Differentially expressed genes included 7 long non-coding RNAs that have not been previously associated with smoking: LINC00599, LINC01362, LINC00824, LINC01624, RP11-563D10.1, RP11-98G13.1, AC004791.2. Secondary analysis of acute smoking (having smoked within 2-h) revealed 5 of the 171 smoking genes demonstrated an acute response above the baseline effect of chronic smoking. Exon-level analyses identified 9 exons from 8 genes with significant differential usage by smoking status, suggesting smoking-induced changes in isoform expression.ConclusionsTranscriptomic changes at the gene and exon levels from whole blood can refine our understanding of the molecular mechanisms underlying the response to smoking.

Transcript Isoform Differences Across Human Tissues Are Predominantly Driven By Alternative Start And Termination Sites Of Transcription

Most human genes have multiple transcription start and polyadenylation sites, as well as alternatively spliced exons. While transcript isoform diversity contributes to shape cellular specificity, it is currently unclear what is the balance of contributions from alternative splicing compared to alternative start and termination sites of transcription. Here, we address this question by analyzing data from the Genotype-Tissue Expression Project. We found tissue-dependent usage of exons for around one-half of expressed genes. Although tissue-dependent splicing was frequent among untranslated exons, it explained less than half of the differences in exon usage across tissues, suggesting that most of these differences were driven by alternative transcription start and termination sites. Analysis of the FANTOMProject data confirmed widespread tissue-dependent usage of alternative transcriptional start sites. Our analysis highlights alternative initiation and termination sites of transcription as the main drivers of isoform diversity across tissues. We also show that most tissue-dependent splicing is unlikely to have consequences at the proteome level.

Reproducible and replicable comparisons using SummarizedBenchmark

Summary: Benchmark studies are widely used to compare and evaluate tools developed for answering various biological questions. Despite the popularity of these comparisons, the implementation is often ad hoc, with little consistency across studies. To address this problem, we developed SummarizedBenchmark, an R package and framework for organizing and structuring benchmark comparisons. SummarizedBenchmark defines a general grammar for benchmarking and allows for easier setup and execution of benchmark comparisons, while improving the reproducibility and replicability of such comparisons. We demonstrate the wide applicability of our framework using four examples from different applications. Availability and implementation: SummarizedBenchmark is an R package available through Bioconductor (http://bioconductor.org/packages/SummarizedBenchmark). Supplementary information: Supplementary data are available at Bioinformatics online.